Research Article
A Blockchain Platform of Crowdsensing for Cloud Reallocation
@INPROCEEDINGS{10.4108/eai.8-12-2023.2344773, author={Hong Jiang and Hui Chen and Yuxin Qiu and Xin Ma and Zhe Zhang}, title={A Blockchain Platform of Crowdsensing for Cloud Reallocation}, proceedings={Proceedings of the 5th Management Science Informatization and Economic Innovation Development Conference, MSIEID 2023, December 8--10, 2023, Guangzhou, China}, publisher={EAI}, proceedings_a={MSIEID}, year={2024}, month={4}, keywords={cloud computing blockchain crowdsensing incentive mechanism supervised lin-ear regression}, doi={10.4108/eai.8-12-2023.2344773} }- Hong Jiang
Hui Chen
Yuxin Qiu
Xin Ma
Zhe Zhang
Year: 2024
A Blockchain Platform of Crowdsensing for Cloud Reallocation
MSIEID
EAI
DOI: 10.4108/eai.8-12-2023.2344773
Abstract
Cloud computing is a technology facilitating broad access to diverse computing ser-vices, predominantly reliant on centralized mechanisms for resource allocation. This study introduces a decentralized platform, harnessing crowdsensing and machine learning, for cloud provisioning and pricing. It involves a blockchain-based trading platform, enabling sellers (primary users) to auction their cloud resources to buyers (secondary users) while considering buyer reputations. To incentivize crowd sensors in gathering and sharing information about available cloud resources, an incentive mechanism is implemented. The pricing is estimated through a supervised machine learning algorithm, specifically linear regression, incorporating critical values and the Vickrey-Clarke-Groves (VCG) algorithm. Results indicate that supervised linear re-gression is a superior approach for enhancing overall utilization. This research pre-sents a robust methodology for integrating cloud computing and machine learning in practical pricing decisions.